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Hadoop Real-World Solutions Cookbook- Second Edition

You're reading from   Hadoop Real-World Solutions Cookbook- Second Edition Over 90 hands-on recipes to help you learn and master the intricacies of Apache Hadoop 2.X, YARN, Hive, Pig, Oozie, Flume, Sqoop, Apache Spark, and Mahout

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Product type Paperback
Published in Mar 2016
Publisher
ISBN-13 9781784395506
Length 290 pages
Edition 2nd Edition
Tools
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Author (1):
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Tanmay Deshpande Tanmay Deshpande
Author Profile Icon Tanmay Deshpande
Tanmay Deshpande
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with Hadoop 2.X FREE CHAPTER 2. Exploring HDFS 3. Mastering Map Reduce Programs 4. Data Analysis Using Hive, Pig, and Hbase 5. Advanced Data Analysis Using Hive 6. Data Import/Export Using Sqoop and Flume 7. Automation of Hadoop Tasks Using Oozie 8. Machine Learning and Predictive Analytics Using Mahout and R 9. Integration with Apache Spark 10. Hadoop Use Cases Index

Performing Atomic export using Sqoop


We have learned in basic database concepts about atomicity, which means doing a complete job or doing nothing. Similarly, if you are exporting data using Sqoop to a table that is very important from the application's point of view and you want make sure that Sqoop should export all data present in HDFS or do nothing, this recipe will help. In this recipe, we are going to see how to ensure atomicity of data export.

Getting ready

To perform this recipe, you should have a Hadoop cluster running with you as well as the latest version of Sqoop installed on it. Here I am using Sqoop 1.4.6. We would also need a MySQL database to be present in the network. Installing Sqoop is easy; by downloading Sqoop tar ball and setting it in the system path. As we are going to import data from MySQL, we would also need to download MySQL connector. Based on your MySQL version, download the right connector jar and copy it into the lib directory of the Sqoop installation.

How to...

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